U.S. Data Engineer

GRIFOLS, S.A.•NC-RTP, CA

23h•Onsite

About The Position

The U.S. Data Engineer designs, builds, and maintains data pipelines and transformation logic that support analytics, reporting, and operational data needs within the U.S. organization. This role partners with the U.S. Data Architect, BI, CRM, Data Governance, and business stakeholders to deliver clean, reliable, well‑structured datasets optimized for analytical use. The U.S. Data Engineer ensures data pipelines meet quality, performance, and compliance standards while supporting continuous improvements to the U.S. data ecosystem.

Requirements

Strong proficiency in SQL and Python.
Hands‑on experience with modern ETL/ELT tools and frameworks (ADF, Databricks, Spark, dbt, Airflow, etc.).
Understanding of data warehouse and lakehouse architectures.
Familiarity with data modeling, semantic layers, and business data structures.
Strong debugging, troubleshooting, and performance‑tuning capabilities.
Ability to work collaboratively across technical and business stakeholders.
Strong written and verbal communication skills.
Bachelor’s degree in Information Systems, Computer Science, Engineering, or related field; or equivalent experience.
Minimum of 5 years of related experience.
Project or technical leadership experience required.

Nice To Haves

Supervisory or management experience preferred.

Responsibilities

Build, maintain, and optimize ETL/ELT data pipelines for ingestion, transformation, and delivery of U.S. data assets.
Develop SQL, Python, and Spark based transformation logic for analytics and reporting needs.
Collaborate with the U.S. Data Architect to design data models and semantic structures aligned to business requirements.
Work with BI to deliver curated, validated datasets supporting dashboards, KPIs, and analytics.
Monitor pipeline performance, troubleshoot failures, and perform root cause analysis.
Implement data quality rules, validation routines, logging, and audit checks.
Support CRM data integration and ensure data consistency across source systems.
Document pipelines, schemas, transformation logic, and operational processes.
Participate in testing and deployment of data enhancements, integrations, and new data sources.
Coordinate with Governance teams to maintain lineage, metadata, and access controls.
Support cloud based engineering activities (Azure preferred).